Capsule Network is a novel and promising neural network in the field of deep learning,
which has shown good performance in image classification by encoding features into …

Capsule Network (CapsNet) is a novel structure for deep neural network, mapping the
region of target instance to vectors and matrices rather than scalars. This process is enabled …

Capsule network is a novel architecture to encode the properties and spatial relationships of
the feature in an image, which shows encouraging results on image classification. However …

Abstract Despite Convolutional Neural Networks (CNNs) based approaches have been
successful in objects detection, they predominantly focus on positioning discriminative …

Capsule network (CapsNet) can recognize the objects by encoding the part-whole
relationships in a way similar to our human perceptual system and has already shown its …

Past few years have witnessed an exponential growth of interest in deep learning
methodologies with rapidly improving accuracy and reduced computational complexity. In …

A capsule network (CapsNet) is a recently proposed neural network model with a new
structure. The purpose of CapsNet is to form activation capsules. In this paper, our team …

Capsule network, which performs feature presentations for classification tasks via novel
capsule forms, has attracted more and more attention. However, its performance on complex …

Nowadays, cancer has become a major threat to people's lives and health. Convolutional
neural network (CNN) has been used for cancer early identification, which cannot achieve …

We propose a novel architecture for object classification, called Self-Attention Capsule
Networks (SACN). SACN is the first model that incorporates the Self-Attention mechanism as …